Cognitive computing. Adopting AI: A guide to revolutionising your customer experience through artificial intelligence

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1 Cognitive computing Adopting AI: A guide to revolutionising your customer experience through artificial intelligence

2 Artificial intelligence and cognitive systems are revolutionising the experiences marketers deliver to customers. New systems allow marketers to anticipate customer needs and use unstructured data to give better insights into your customers behaviours so you can pre-empt their desires. IBM s Joe Cosentino says the main use-cases for artificial intelligence and cognitive systems fall into three categories. Cognitive discovery, which is about answering questions Cognitive conversations, where people interact with systems in a conversational way Cognitive extension, where systems look for signals in data that can be used to add value to other data (such as automatically tagging images with metadata to make them easier to find) For marketers, AI and cognitive computing systems like IBM s Watson, which can read 800 million pages every second, have given rise to systems that can process data in near real-time to give instant feedback. And it s not just written text. Watson can analyse the spoken word in many languages. That capability, said Cosentino means Watson can be applied to a business to accelerate the go to market and insights they can derive. The most practical usage is in using cognitive as a trusted advisor. That advisor role can be inside the business, supporting marketers as they seek to understand the massive volumes of rapidly arriving data they contend with every day. And it extends to helping customers through their journey, supporting them as they make purchasing decisions or look for support. The most practical usage is in using cognitive as a trusted advisor. Joe Cosentino, Worldwide CSP Lead, IBM Watson Customer Engagement Page 2

3 What can cognitive systems do for marketers? Watson s ability to analyse vast volumes of structured and unstructured data gives it the ability to be used in myriad ways. It can be used to power chatbots, or virtual salesperson or support agents, that can respond to customer queries, in real time, in order to deflect routine requests that take up the time of call centre staff. Or, it can be used to look at social media data to conduct detailed analysis of what people are saying about your company or your competitors. It can even detect sarcasm. Cognitive systems can also recognise objects in images, giving them the ability to see the contents of a photo and create metadata tags that make it easy to find the shot you re after. And while Watson doesn t necessarily make decisions on your behalf, it can give you better information, by reviewing more data than a human can possibly manage, to give you insights that help you make better decisions. Carlie Lau from ING Direct said cognitive computing is critical as it allows challenger brands to deliver a better customer experience more efficiently than larger and more highly resourced incumbent competitors. How can you leverage AI systems like Watson? Businesses can leverage the Watson platform by integrating its capabilities using APIs (Application Programming Interfaces). These are software tools that allow you to create applications that hook into Watson. For example, you can use Watson s visual recognition API to look at a collection of photos, identify the content and automatically add metadata tags. Or you can direct Watson to listen to voice recordings and tell you which calls came from unhappy customers. One of the obvious areas cognitive computing and AI can reshape a business is influencing the customer journey and experience. By recognising what a customer wants, cognitive systems can deliver a guided experience to customers that blends the personalised service of a bricks and mortar store with the convenience of shopping online. Customers can move through a transaction in a non-linear fashion to complete a transaction how they want. Non-linear customer journeys are the reality, said Jason Davey, the Head of Digital at Ogilvy. And it s important to understand the customer s emotions something that AI can help recognise through its ability to interpret vast volumes of unstructured data. But, he said it can go further, citing a company focusing on age-related healthcare medications that had appointed an AI to its board of directors, it s possible to use cognitive computing, AI and machine learning to guide people and assist them with decision making. But while all this sounds good, making the rubber hit the road brings its own challenges. Page 3

4 Getting started Although machine learning and cognitive systems can solve complex problems and assist with challenging business processes, implementing this technology doesn t have to be a gargantuan task. The trick is to find a specific business problem and look at how cognitive systems like Watson can solve it. Cameron Wall is the founder and CEO of RainCheck a company focussed on bridging the gap between online and offline customer experiences. He said that in retail apparel, customers do about 90% of their research online but 90% of the transactions are completed offline. By using cognitive computing services from IBM s Watson platform, they are able to use data to hone in on the specific needs of each customer and narrow that differential. Lau said ING Direct started by taking small steps and not jumping into the deep end with AI. ING Direct started with the Unica marketing platform and used that to automate marketing communications based on specific triggers. As a challenger brand, she said ING Direct doesn t have the resources to spend large amounts of capital to re-platform the organisation. Lau said it was about picking off a project, getting the ROI and moving along to whatever is next. One area we ve really focussed on is building out the customer marketing area. There s been a shift to deepen the customer relationship. It absolutely makes sense to focus on that area. We ve been looking to build up that ability to communicate with customers, said Lau. They are adding machine learning, taking small steps as they go rather than trying to embark on a massive undertaking. Continual progress, along a planned path and learning along the way are critical. Jim Stirewalt, Vice President, IBM Watson Customer Engagement through his involvement across IBM s various business forums, identified several use-cases that highlight where companies have achieved great success with limited effort. Cathay Pacific used AI to detect and solve issues with their booking system in real-time. Gift service 1800-Flowers created a personalised AI-based concierge to recommend gifts based on who they are for, what s trending, price and other criteria based on what the system learns about you. Davey said a good place to start is to focus on the areas of greatest customer dissatisfaction. By examining the customer journey and looking up- and down-stream, there will be opportunities for improvement and perhaps a new model or way of working. This is the example, Davey says, Uber and AirBNB took. They looked at the customer experience in their respective sectors and transformed it by taking a data-centric approach that leveraged machine learning and AI. It s about applying technology to customer-centric thinking. One area we ve really focused on is building out the customer marketing area. There s been a shift to deepen the customer relationship. It absolutely makes sense to focus on that area. We ve been looking to build up that ability to communicate with customers. Carlie Lau, Head of Customer Intelligence, ING Direct Australia Page 4

5 Frontline staff can benefit One of the other ways this technology can be useful isn t just to deliver great service but to make it easier for frontline staff to deliver great service consistently said HCF s head of data analytics and research, Scott Verrall. Cognitive systems, he says, allow business to take some of the more mundane and repetitive tasks away from staff so they can focus on more high-value tasks. This is about helping our people who do a great job now do an even better job in future, said Verrall. He said there were two main areas HCF looked at for these emerging technologies. The first is where there are large spends that pushed out on a spray and pray type approach. You can apply this to programmatic where you can get targeted, learn and adjust in real time to save money and get a better outcome. The second is where a more concrete insight is required rather than a subjective view. Verrall said, while it s possible to gain some insight by talking to people about the efficacy of a process, you can use a tool such as Watson to listen to 25,000 calls and bring out something more concrete that has broader application. Coop Danmark used to run sales at the end of each month where items were discounted by 40% to 70%. However, by using cognitive systems, they were able to better target the sales by location and time resulting in a sales uplift of around 20% - exceeding the 10% target they had initially set. These sorts of systems drive, what Wall called, contextual commerce; delivering what customers want, when they want it in a way that makes it easy for them to complete a transaction. Business and executive engagement are critical One of the keys to getting a business to invest in cognitive systems, AI and machine learning, said Verrall, is to get executive engagement and sponsorship. It needs a champion, he said. Sometimes it comes down to Will we get a return on the dollars versus what s the opportunity cost of pursuing this?. Sometimes it s about changing the conversation to Do we want to play catch up or Do we want to play leapfrog? Do we want to be as good as the other people who are already in front of us or Do we want to set a new benchmark? What does that say about our brand to our customers?. With technology taking an increasing role in marketing, particularly in the fields of AI, machine learning and cognitive computing, it can be challenging to work out the best way to engage with these changes and to ensure people are empowered, rather than threatened. The keys are to look for processes that care for your customers personnel challenges and then use the technology to support people to reach more positive outcomes. This allows the new technologies to be applied to resolve specific problems rather than driving a massive, organisation-wide system reengineering project which can be expensive and risky. This will allow senior management to see the value and support further expansion of the technology. As the role of marketers become increasingly data driven, and the volume and velocity of that data continues to increase, artificial intelligence and cognitive systems such as IBM s Watson can assist by directly interacting with customers to support them through transactions, automatically managing processes such as image tagging by being able to recognise what s in a photo, and analysing and providing insights into massive volumes of structured and unstructured data. The key is to focus on specific problems and then look to solve those, rather than try to apply the technology to everything all at once. That will allow you to score some quick wins so you can garner executive support and apply cognitive systems and AI to more complex problems. This is about helping our people who do a great job now do an even better job in future. Scott Verrall, Head of Data Analytics and Research, HCF Page 5

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